基于广义阈值补充的自适应矢量量化

J. Fowler, S. Ahalt
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引用次数: 15

摘要

本文提出了一种用于非平稳信号编码的自适应矢量量化(AVQ)算法。这种新算法,广义阈值补充(GTR),不同于先前的AVQ算法,因为它具有明确的,在线考虑速率和失真。在确定最近邻码字和决定是否更新码本时,都使用了速率失真代价准则。结果表明,对于图像序列的编码,(1)在相同速率下,大多数AVQ算法的失真率远低于非自适应VQ算法(约1.5 bits/pixel);(2)在低速率下,GTR算法的失真率性能明显优于先前的AVQ算法,是唯一一个实现低于1.0 bits/pixel的编码率的算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Adaptive vector quantization using generalized threshold replenishment
In this paper, we describe a new adaptive vector quantization (AVQ) algorithm designed for the coding of nonstationary sources. This new algorithm, generalized threshold replenishment (GTR), differs from prior AVQ algorithms in that it features an explicit, online consideration of both rate and distortion. Rate-distortion cost criteria are used in both the determination of nearest-neighbor codewords and the decision to update the codebook. Results presented indicate that, for the coding of an image sequence, (1) most AVQ algorithms achieve distortion much lower than that of nonadaptive VQ for the same rate (about 1.5 bits/pixel), and (2) the GTR algorithm achieves rate-distortion performance substantially superior to that of the prior AVQ algorithms for low-rate coding, being the only algorithm to achieve a rate below 1.0 bits/pixel.
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